The demand for multimedia streaming over mobile networks has been steadily increasing in the past several years. For instance, it has become common for mobile users to stream full TV episodes, sports events, and movies while on the go. Unfortunately, this growth in demand has strained the wireless networks despite the significant increase in their capacities with recent generations. It has also caused a significant increase in the energy consumption at mobile terminals. To overcome these challenges, we first present a novel hybrid unicast and multicast streaming algorithm to minimize the overall energy consumption of mobile terminals as well as the traffic load within cellular networks. Next, we introduce the idea of dynamically configuring cells in mobile networks to form single frequency networks based on the video popularity and user distribution in each cell. We formulate the transmission scheduling problem in such complex networks, and we then present optimal and heuristic solutions to maximize the number of served multimedia streams. Through detailed packet-level simulations, we assess the performance of the aforementioned algorithms with respect to the average service ratio, energy saving, video quality, frame loss rate, initial buffering time, rate of re-buffering events, and bandwidth overhead. Finally, we extend our research to formulate the transmission scheduling problem for adaptive streaming in the emerging heterogeneous cellular networks. We propose an algorithm for the cells in a heterogeneous network to self organize their radio resource allocations in order to minimize the inter-cell interference and increase the average data rate received by mobile terminals. Then we evaluate its performance through extensive simulations of various heterogeneous configurations.
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